MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

&nbsp;

MIT World Peace University

School of Electronics & Communication Engineering

Low power wide area network (LPWAN) is a promising solution for long range and low power Internet of Things (IoT) and machine to machine (M2M) communication applications. The LPWANs are resource-constrained networks and have critical requirements for long battery life, extended coverage, high scalability, and low device and deployment costs. There are several design and deployment challenges such as media access control, spectrum management, link optimization and adaptability, energy harvesting, duty cycle restrictions, coexistence and interference, interoperability and heterogeneity, security and privacy, and others. LPWAN Technologies for IoT and M2M Applications is intended to provide a one-stop solution for study of LPWAN technologies as it covers a broad range of topics and multidisciplinary aspects of LPWAN and IoT. Primarily, the book focuses on design requirements and constraints, channel access, spectrum management, coexistence and interference issues, energy efficiency, technology candidates, use cases of different applications in smart city, healthcare, and transportation systems, security issues, hardware/software platforms, challenges, and future directions. © 2020 Elsevier Inc. All rights reserved.

Engineering and Technology

World University root node

LPWAN Technologies for IoT and M2M Applications

Recently, optical network on chip (ONoC) has attracted the attention of researchers as a promising technology for low power and high bandwidth on chip communication. ONoC improves the computational efficiency of multi-core processors and chips. However, their performance suffers from power losses and limited scalability. In this paper, we present two innovative designs of five port non-blocking ONoC routers constructed by using micro-ring resonators and waveguides for low power losses and the optimum number of components. We compared the performance of the designed routers with previously reported optical routers for the power insertion loss and the requirement of micro-ring resonators. The result shows that proposed optical routers have the lowest power losses and require a lower number of micro-ring resonators. First proposed router has 1.3% lower average loss and 9.8% lower maximum port to port loss as compared to Cygnus router. The second proposed router has 4.8% lower average loss than Cygnus router. The results also show that the performance of both the routers is far better than the crossbar router. The second proposed router requires only fifteen micro-ring resonators, that is 6% lower than Cygnus router.

Springer International Journal of Information Technology, vol. 12, pp. 91-96, 2020.

Optimized Designs of Low Loss Non-Blocking Optical Router for ONoC Applications

Due to rapid growth in urban population and advances in the automotive industry, the number of vehicles is increasing exponentially, posing the parking challenges. Automated parking systems provide efficient and optimal parking solution so that the drivers can have hassle free and quick parking. One of the demanding requirements is the design of smart parking systems, not only for comfort but also of economic interest. With the advancements in the Internet of Things (IoT), wireless sensors-based parking systems are the promising solutions for the deployment. Optimal positioning of IoT enabled wireless sensor nodes in the parking area is a crucial factor for the efficient parking model with the lower cost. In this paper, we propose a novel multi-objective grey wolf optimization technique for node localization with an objective to minimize a localization error. Two objective functions are considered for distance and geometric topology constraints. The proposed algorithm is compared with other node localization algorithms. Our algorithm outperforms the existing algorithms. The result shows that localization error is reduced up to 17% in comparison with the other algorithms. The proposed algorithm is computationally efficient due to the choice of fast converging parameters.

IEEE Transactions on Intelligent Transportation Systems

GWO Model for Optimal Localization of IoT-Enabled Sensor Nodes in Smart Parking Systems

Concept of Green communication is emerged from negative impact of wireless communication on the environment. Green communication through green networking can be implemented for making cellular network energy efficient. Green network system can be designed by using energy efficient networking approaches with minimum usage of radio resources. Observations from the recent studies suggest that a base station is the principal contributor of the energy consumption in cellular network. This paper presents a brief survey of different types of base stations and various methods to enhance the energy efficiency of a cellular network base station. Lastly, this paper is focusing on a brief introduction of power saving algorithms. © 2019 IEEE.

International Conference on Innovative Technology for Humanity(IEEE PuneCon 2019),18th Dec. 2019, Published in IEEE Xplore 02 June 2020, ISBN: 978-1-7281-1924-3

Energy Efficient Cellular Network Base station:A survey

Background and Objective: Random Black Hole (BH) attack significantly degrades MANET’s performance. For strategic applications, the performance parameters like Packet Delivery Ratio, Routing Overheads, etc. are important. The objectives are: (a) To model random BH attack, (b) To propose a routing strategy for the protocol to mitigate random BH attack, (c) To evaluate and compare the network performance of modified protocol with the standard protocol. Methods: The random BH attack is modelled probabilistically. The analysis is carried out by varying Black Hole Attack (BHA) time as Early, Median, Late occurrences and mix of these three categories. The blocking performance is also analysed by varying the percentages of malicious presence in the network. Normal Optimized Link State Routing (OLSR) protocol is used to simulate the MANET performance using a typical medium size network. The protocol has then been modified using TrustConfidence aware routing strategy, named as TCAOLSR, with a view to combat the degradations due to the random BH attack. Results: The random behavior of Black Hole attack is analyzed with all the possible random parameters, like deployment of mobile nodes, number of malicious nodes and timing instances at which these nodes change their state. From the results of individual type-Early, Median and Late, it is observed that the TCAOLSR protocol gives stable performance for Packet Delivery Ratio (PDR) and Routing Overheads (RO), whereas for OLSR protocol PDR gradually reduces and RO increases. For individual and mix type, Average Energy Consumption (AEC) per node increases marginally for TCAOLSR protocol. For the mix type, PDR for TCAOLSR is 40-60% better whereas RO for TCAOLSR is very less compared to OLSR protocol. The efficacy of the TCAOLSR protocol remains stable for different categories of BH attack with various percentages of malicious nodes compared to OLSR with the same environment. Conclusion: Simulations reveal that the modified protocol TCAOLSR, effectively mitigates the network degradation for Packet Delivery Ratio and Routing Overheads considerably, at the cost of a slight increase in Average Energy Consumption per node of the network. Efficacy of the OLSR and TCAOLSR protocols has also been defined and compared to prove robustness of the TCAOLSR protocol. © 2020 BenthamScience Publishers.

International Journal of Sensors, Wireless Communications and Control

Random black hole attack modelling and mitigation using trustconfidence aware olsr in manets for private data communications

Background: The performance of Mobile Ad-hoc Networks get severely degraded due to various attacks including Selfish Behaviour attack. The detection of malicious nodes and avoidance of such nodes for data forwarding is important to enhance the MANET’s performance.Methods: A probabilistic model based on Single Sided Laplacian distribution for the random ON/OFF switching time of this attack is proposed. The model is used to make appropriate decisions regarding assignment of trust levels to suspicious nodes. The proposed protocol, based on this trust along with Confidence values of nodes, referred to as OLSRT-C protocol is used to select the optimum path for data forwarding. Simulations are carried out using Network Simulator NS2.35.Results: The random behavior of Selfish Behaviour attack is analyzed by considering all the possible random parameters. The random deployment of mobile nodes, number of malicious nodes, number of times the malicious nodes switch and timing instances at which these nodes change their states are considered. From the results, it is observed that, the OLSRTC protocol gives stable performance for Packet Delivery Ratio and Routing Overheads whereas for OLSR protocol, Packet Delivery Ratio gradually reduces and Routing Overheads increase, for percentage of malicious nodes increase from 10% to 50%. For OLSRT-C protocol, Average Energy Consumption per node increases marginally compared to OLSR protocol.Conclusion: The proposed OLSRT-C protocol successfully mitigates randomized Selfish Behaviour attack with marginal increase in the Average Energy Consumption per node. The Protocol Efficacy for OLSRT-C protocol is much higher compared to OLSR protocol.

Intrenational journal of sensor wireless communications and network

Modelling of Random selfish behaviour attack using single sided laplacian distribution and performance evaluation for high security communications in mobile adhoc network

As mentioned in the global two-wheeler market report, the two-wheeler market is projected to surpass $ 125 billion by 2024. According to WHO statistics, approximately 1.35 million people die each year as a result of road traffic crashes. And more than half of those are pedestrians, cyclists, and motorcyclists. Correct helmet use can lead to a 42 percent reduction in risk of fatal injuries and a 69 percent reduction in the risk of head injuries. These are concerning statistics. These growing numbers call forth new and upcoming technological advancements concerning the safety of the users. The main reason behind coming up with this smart helmet is the very issue of safety. The main objective of the project is to build a smart system which is integrated with sensors and modules for the safety of the user. While working on improving the safety of riders, it was ensured that its aesthetics and ergonomics are not compromised. © 2020 IEEE.

IEMTRONICS 2020 - International IOT, Electronics and Mechatronics Conference, Proceedings

Design and finite element analysis of IoT based smart helmet

Narrowband-Internet of Things (NB-IoT) is a standard-based low-power wide-area network (LPWAN) technology developed to connect a wide range of new IoT devices and services. The NB-IoT will improve the power consumption of user devices, system capacity, and spectrum efficiency. It is able to be loaded by major mobile equipment and module manufacturers, and indeed it will be existing to be adaptable with any cellular mobile network’s generations. It also benefits from all the security and privacy features of mobile networks. In this chapter, fundamental key aspects of NB-IoT are investigated and the features of NB-IoT and technical properties are proposed in addition to the theoretical concepts. A detailed overview of the current NB-IoT-related technologies such as Long-Term Evolution for Machines (LTE-M), Third Generation Partnership Project (3GPP), enhanced Machine Type Communication (eMTC) and ultralow power technologies is discussed. This chapter will also provide details of different applications related to NB-IoT such as smart grid, smart cities, and smart industry. Security issues and other deployment considerations will be explored. © 2020 Elsevier Inc. All rights reserved.

NB-IoT: concepts, applications, and deployment challenges

The major challenges faced by visually impaired are mobility and orientation during their navigation. For safe navigation of visually impaired, an assistive system that can estimate the distance between visually impaired and the obstacle (pedestrian) and generate an alert signal for the user is required. This paper presents a prototype of obstacle (pedestrian) distance estimation and alert generation system using a defocus measure for visually impaired. Initially, the video frames are extracted and preprocessed. Further, the feature points are detected using the Shi Tomasi corner detector. The feature points in the subsequent frames are tracked using Kanade-Lucas-Tomasi (KLT). Region of interest of size 20 x 20 pixels is extracted around every feature point and the defocus measure is computed by using first level wavelet decomposition. For a typical camera, the defocus measure is a function of the distance between camera and obstacle and therefore can be used to estimate distance. The algorithm is implemented on the ARM Cortex-A7 platform using Embedded Linux and open-source computer vision library. The algorithm is tested on a USB web camera and 10 videos. This method is proved to be effective forobstacle distance measurement. The average absolute error of 0.0081m with a standard deviation of 0.02775 and the average error of 0.347% with a standard deviation of .63583 is observed for camera 1. The average absolute error of -0.21m with a standard deviation of 0.359 and the average error of -4.69% with a standard deviation of 6.99is observed for camera 2.The alert signal is generated at a distance of 3.33m for visually impaired during the navigation.The repeatability of the prototype is 90%.

International Journal of Advanced Science and Technology

Development of Prototype for Obstacle Detection for Visually Impaired using Defocus Measure

Face and facial components are the most significant pieces of evidence used in forensic applications. Component-based recognition and age-invariant face recognition are the key factors in forensic face recognition. A major challenge during a forensic investigation is the association of facial components with a relevant face and this paper addresses this concern using the proposed transfer learning methodology. Research has been carried out treating facial components and the face as individual and separate entities. However, they share common auxiliary information which is exploited to bring the face and facial components in a common subspace in the proposed method. This facilitates transfer of knowledge gained from a face and classification of facial components of a person using the same subspace. Stability and invariant features of the facial components catalyze a solution for the problem of recognition. Convolutional neural network (CNN) is used to extract the features of the biometrics and then they are given to a regularization framework for reducing the probability distribution difference between them. The system is trained using the face and facial components and then tested using either the full-face or individual facial components. For the transfer, the proposed Fisher linear discriminant analysis and locality preserving projection, a convolutional neural network-based algorithm gives 91% and 90% accuracy, respectively, which outperforms the Histogram of Gradient and Gabor methods for predicting an association. © 2020, Springer Nature Singapore Pte Ltd.